mirror of
https://github.com/Mintplex-Labs/anything-llm.git
synced 2024-11-19 12:40:09 +01:00
65 lines
2.1 KiB
JavaScript
65 lines
2.1 KiB
JavaScript
const OpenAI = require("openai");
|
|
|
|
/**
|
|
* @type {import("openai").OpenAI}
|
|
*/
|
|
const client = new OpenAI({
|
|
baseURL: "http://localhost:3001/api/v1/openai",
|
|
apiKey: "ENTER_ANYTHINGLLM_API_KEY_HERE",
|
|
});
|
|
|
|
(async () => {
|
|
// Models endpoint testing.
|
|
console.log("Fetching /models");
|
|
const modelList = await client.models.list();
|
|
for await (const model of modelList) {
|
|
console.log({ model });
|
|
}
|
|
|
|
// Test sync chat completion
|
|
console.log("Running synchronous chat message");
|
|
const syncCompletion = await client.chat.completions.create({
|
|
messages: [
|
|
{
|
|
role: "system",
|
|
content: "You are a helpful assistant who only speaks like a pirate.",
|
|
},
|
|
{ role: "user", content: "What is AnythingLLM?" },
|
|
// {
|
|
// role: 'assistant',
|
|
// content: "Arrr, matey! AnythingLLM be a fine tool fer sailin' the treacherous sea o' information with a powerful language model at yer helm. It's a potent instrument to handle all manner o' tasks involvin' text, like answerin' questions, generating prose, or even havin' a chat with digital scallywags like meself. Be there any specific treasure ye seek in the realm o' AnythingLLM?"
|
|
// },
|
|
// { role: "user", content: "Why are you talking like a pirate?" },
|
|
],
|
|
model: "anythingllm", // must be workspace-slug
|
|
});
|
|
console.log(syncCompletion.choices[0]);
|
|
|
|
// Test sync chat streaming completion
|
|
console.log("Running asynchronous chat message");
|
|
const asyncCompletion = await client.chat.completions.create({
|
|
messages: [
|
|
{
|
|
role: "system",
|
|
content: "You are a helpful assistant who only speaks like a pirate.",
|
|
},
|
|
{ role: "user", content: "What is AnythingLLM?" },
|
|
],
|
|
model: "anythingllm", // must be workspace-slug
|
|
stream: true,
|
|
});
|
|
|
|
let message = "";
|
|
for await (const chunk of asyncCompletion) {
|
|
message += chunk.choices[0].delta.content;
|
|
console.log({ message });
|
|
}
|
|
|
|
// Vector DB functionality
|
|
console.log("Fetching /vector_stores");
|
|
const vectorDBList = await client.beta.vectorStores.list();
|
|
for await (const db of vectorDBList) {
|
|
console.log(db);
|
|
}
|
|
})();
|